Kernel Profiling
ZJLi2013/awesome-kernel-skills
Profile GPU kernels using NCU (NVIDIA) or rocprof (AMD) to collect performance metrics.
A skill your agent uses when the user is doing hands-on DOCA Rivermax work on a BlueField DPU or ConnectX host — standing up docarmaxinstream (receive) sessions for timing-precise media-over-IP…
$ npx skills add NVIDIA/skills --skill doca-rmax -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install NVIDIA/skills doca-rmax --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/doca-rmax .claude/skills/doca-rmax && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "doca-rmax" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-rmax into .claude/skills/doca-rmax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-rmax", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/NVIDIA/skills/tree/main/skills/doca-rmaxType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add NVIDIA/skills --skill doca-rmax -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install NVIDIA/skills doca-rmax --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/doca-rmax .agents/skills/doca-rmax && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "doca-rmax" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-rmax into .agents/skills/doca-rmax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-rmax", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill doca-rmax -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install NVIDIA/skills doca-rmax --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/doca-rmax .cursor/skills/doca-rmax && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "doca-rmax" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-rmax into .cursor/skills/doca-rmax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-rmax", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/NVIDIA/skills.git --path skills/doca-rmax--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add NVIDIA/skills --skill doca-rmax -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install NVIDIA/skills doca-rmax --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/doca-rmax .gemini/skills/doca-rmax && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "doca-rmax" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-rmax into .gemini/skills/doca-rmax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-rmax", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install NVIDIA/skills doca-rmaxInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add NVIDIA/skills --skill doca-rmax -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/doca-rmax .github/skills/doca-rmax && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "doca-rmax" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-rmax into .github/skills/doca-rmax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-rmax", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add NVIDIA/skills --skill doca-rmax -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install NVIDIA/skills doca-rmax --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/NVIDIA/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/doca-rmax .opencode/skills/doca-rmax && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "doca-rmax" agent skill from https://github.com/NVIDIA/skills/tree/main/skills/doca-rmax into .opencode/skills/doca-rmax/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "doca-rmax", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
doca-rmaxA skill your agent uses when the user is doing hands-on DOCA Rivermax work on a BlueField DPU or ConnectX host — standing up docarmaxinstream (receive) sessions for timing-precise media-over-IP…
Doca Rmax is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Use this skill when the user is doing hands-on DOCA Rivermax work on a BlueField DPU or ConnectX host — standing up docarmaxinstream (receive) sessions for timing-precise media-over-IP (SMPTE ST 2110 video/audio, market data, scientific feeds), confirming the Rivermax SDK + license precondition before any DOCA-side code, running docarmaxgetsupported capability queries, pairing with doca-eth queues and doca-flow steering, or debugging DOCAERROR from a Rivermax call. Trigger even when the user does not explicitly…
Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files (for example `BENCHMARK.md`, `CAPABILITIES.md` and `SKILLCARD.yaml`). Compatibility notes: Requires DOCA SDK at /opt/mellanox/doca on Linux (Ubuntu 22.04/24.04 or RHEL/SLES) with a BlueField DPU or ConnectX NIC, AND the separately- installed NVIDIA…
It sits in Development, covering Stock and market analysis. It works with NVIDIA AI Platform. The repository describes itself as: Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end. The licence is Apache-2.0.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 0e0d506. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Requires DOCA SDK at /opt/mellanox/doca on Linux (Ubuntu 22.04/24.04 or RHEL/SLES) with a BlueField DPU or ConnectX NIC, AND the separately- installed NVIDIA Rivermax SDK with a valid Rivermax license readable by the user — DOCA does NOT bundle Rivermax. Reads the local install via `pkg-config doca-rmax`; route Rivermax SDK install/license questions to the public Rivermax guide.
From compatibility in the SKILL.md frontmatter.
Doca Rmax loads about 4.6k tokens when it runs. Until then it costs about 255 tokens; SKILL.md has 2,010 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
expects (typically sudo or `mlnx`-group membership to open aAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from NVIDIA/skills at commit 0e0d506, republished under its Apache-2.0 licence (© NVIDIA). 2,010 words, ~4,568 tokens.
.claude/skills/doca-rmax/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.Where to start: This skill assumes DOCA is already installed,
AND that the NVIDIA Rivermax SDK is separately installed with a
valid Rivermax license present on the host. The agent's FIRST
action on any Rivermax question is to confirm both — without
Rivermax SDK + license, doca-rmax cannot function regardless
of how clean the DOCA-side code is, and this is the #1 first-app
confusion (DOCA does not bundle Rivermax; it wraps it). Open
TASKS.md if the user wants to do something
(configure / build / modify / run / test / debug); open
CAPABILITIES.md when the question is what
can DOCA Rivermax express on this version + this Rivermax
install. If the user has not installed DOCA yet, route to
doca-setup first; for the Rivermax
SDK + license install itself, route to the public DOCA Rivermax
guide (slug DOCA-Rivermax) via
doca-public-knowledge-map.
If the user is asking "how do I get packets to land on my
Rivermax input stream at all", the answer is layered:
doca-rmax is the Rivermax integration surface,
doca-eth is the queue surface that
carries the packets, and doca-flow
is the steering surface that directs them.
The CLASSES of DOCA Rivermax questions this skill is built to answer, each with one worked example. The agent should treat the class as the load-bearing piece — the worked example is a single instance.
doca-rmax on this host?" — worked
example: "the public docs mention doca-rmax; is it
usable without doing anything else?". Answered by the
Rivermax-SDK + license precondition rule in
CAPABILITIES.md ## Safety policyTASKS.md ## configure step 1, which
routes the install-side question to the public Rivermax guide
via
doca-public-knowledge-map
and refuses to recommend a fallback to doca-eth alone that
would silently lose the timing properties.TASKS.md ## configure +
CAPABILITIES.md ## Capabilities and modes
input stream capability table.doca_rmax_get_*_supported query do I have to call before
picking a PTP clock or hardware packet-placement order?" — worked
example: "can this device + this Rivermax install use
ST 2110-20 sequence-number placement?". Answered by the
capability-query rule in
CAPABILITIES.md ## Capabilities and modesTASKS.md ## configure.CAPABILITIES.md ## Safety policyTASKS.md ## configure step 1, which
routes the steering side to
doca-flow, the queue side to
doca-eth, and the license side
back to the Rivermax-side precondition.CAPABILITIES.md ## Capabilities and modesCAPABILITIES.md ## Version compatibility,
which adds the Rivermax-side version is a second axis rule
on top of the canonical DOCA version-handling chain in
doca-version.DOCA_ERROR_* from a Rivermax call mean and
which layer caused it?" — worked example:
"DOCA_ERROR_NOT_SUPPORTED from doca_rmax_init()".
Answered by the Rivermax overlay on the
cross-library taxonomy in
CAPABILITIES.md ## Error taxonomyTASKS.md ## debug that escalates to
doca-debug, and which preserves
the installed header's call-specific mapping: init-time
_NOT_SUPPORTED routes first to Rivermax SDK / license checks;
later errors are interpreted from the exact failing call rather
than generalized into a license diagnosis.This skill serves external developers building applications
that consume the DOCA Rivermax integration — i.e., users whose
code calls doca_rmax_* (directly in C/C++, or through
FFI/bindings from another language) to drive timing-precise
media-over-IP streams (SMPTE ST 2110, real-time market data,
high-throughput scientific instrument streams) on top of a
separately-installed NVIDIA Rivermax SDK on a BlueField or
ConnectX host. It is not for NVIDIA developers contributing to
DOCA Rivermax itself, and it is not for users who want
best-effort packet I/O — for that, route to
doca-eth directly.
Language scope. DOCA Rivermax ships as a C library with
pkg-config module name doca-rmax. The shipped samples
live under /opt/mellanox/doca/samples/doca_rmax/ and are
written in C. C and C++ consumers are the canonical case; the
worked examples in TASKS.md assume that path. Other-language
consumers (Rust, Go, Python, …) consume the same *.so through
FFI or language-specific bindings; the skill's contribution in
that case is to keep the precondition rule (Rivermax SDK +
license), per-stream lifecycle, capability-discovery,
permission, scheduling-discipline, and error-taxonomy guidance
language-neutral, and to route the agent to the public C ABI as
the authoritative surface that any wrapper will eventually call.
Load this skill when the user is doing hands-on DOCA Rivermax work, in any language. Concretely:
doca-rmax cannot be
used; pick a different library", not "let's try and see what
fails".doca_rmax_init() / doca_rmax_release(), then creating a
doca_rmax_in_stream (receive) context with
doca_rmax_in_stream_create() on a doca_dev opened against a
physical port, a representor, or an SF, and converting it via
doca_rmax_in_stream_as_ctx() before doca_ctx_start(). The
public DOCA Rivermax API is receive-only — there is no
transmit/output stream object.doca_rmax_get_*_supported query.doca_rmax_in_stream_set_* and querying device + Rivermax
capability via the doca_rmax_get_*_supported family before
assuming PTP-clock or hardware packet-placement-order support.doca-eth queue surface
that carries the packets and the doca-flow rules that
steer them — Rivermax does not program steering itself.doca-public-knowledge-map).DOCA_ERROR_* returned from a Rivermax call
(lifecycle vs. license / permission vs. capability vs.
driver-below) where the cause may live in the DOCA-side
wrapper, the underlying Rivermax stack, or the licensing
layer.Do not load this skill for general DOCA orientation, for
installing DOCA itself, for installing the Rivermax SDK or
managing the Rivermax license file (those live in the public
Rivermax SDK guide reachable through
doca-public-knowledge-map),
for best-effort packet I/O without timing requirements (use
doca-eth directly), or for pure
host-side data processing without networking. For DOCA
documentation orientation, use
doca-public-knowledge-map.
This is a thin loader. The body keeps only the orientation needed to pick the right next file. The substantive Rivermax-specific material lives in two companion files:
CAPABILITIES.md — what DOCA Rivermax can express on this
version and this Rivermax SDK install: the
Rivermax-as-hard-dependency rule, the receive-only
doca_rmax_in_stream object model, the capability-query surface
(doca_rmax_get_*_supported), the Rivermax error taxonomy
(mapped onto the cross-library DOCA_ERROR_* set, with
Rivermax-specific causes called out per row), the
observability surface (per-stream progress engine events,
capability snapshots, Rivermax-side license + driver state),
and the safety policy that gates the Rivermax-SDK-present /
license-present / device-access / scheduling-discipline
preconditions.TASKS.md — step-by-step workflows for the six in-scope
Rivermax verbs: configure, build, modify, run,
test, debug. Plus a Deferred task verbs block that
points out-of-scope questions (installing Rivermax,
managing the license, programming steering, programming the
underlying queue) at the right next skill, and a Command appendix of the recurring commands the agent reaches for.The skill assumes a host or BlueField where DOCA is already
installed at the standard location, the NVIDIA Rivermax SDK is
installed at its expected location with a valid license, and
the user has the privileges their public install profile
expects (typically sudo or mlnx-group membership to open a
doca_dev against a port). It does not cover installing DOCA —
that path goes through
doca-setup. It does not cover
installing Rivermax or its license — that path goes through the
public Rivermax SDK guide reachable through
doca-public-knowledge-map.
This skill is agent guidance, not a samples or templates bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:
/opt/mellanox/doca/samples/doca_rmax/<name>/.
The agent's job is to route the user to those files and
prescribe a minimum-diff modification on them via the
universal modify-a-sample workflow in
doca-programming-guide,
layered with the Rivermax-specific overrides in
TASKS.md ## modify.meson.build,
CMakeLists.txt, Cargo.toml, …) parked inside the skill.
The agent constructs the build manifest in the user's
project directory against the user's installed DOCA, where
pkg-config --modversion doca-rmax is the source of
truth.doca_rmax_get_*_supported for capability discovery,
receive-only doca_rmax_in_stream session objects driven by the
standard DOCA Core context lifecycle). Exact Rivermax
symbol names are install-bound and Rivermax-SDK-version-
bound; the agent should read them from the installed headers
at $(pkg-config --variable=includedir doca-common) and from the
public DOCA Rivermax guide rather than rely on agent memory.samples/, bindings/, or reference/ subtree of
any kind. A mock or incomplete artifact in this skill's
tree, even one labeled "reference", is misleading: users
will read it as buildable.SKILL.md first to confirm the user's question is
in scope and that the Rivermax-SDK + license
precondition has been considered.Both companion files cross-link to each other,
doca-version for the canonical
DOCA version-handling rules (Rivermax adds a Rivermax-SDK-
version axis on top),
doca-eth for the queue surface
that carries the packets,
doca-flow for the steering side
that decides which packets land on which queue, and
doca-public-knowledge-map
whenever the right answer is "look it up in the public
Rivermax SDK guide or the installed package layout" rather
than "Rivermax-integration-specific guidance".
doca-public-knowledge-map —
the routing table for every public DOCA documentation source
and the on-disk layout of an installed DOCA package. The
Rivermax URL slug is DOCA-Rivermax; the public Rivermax SDK
guide (separate product) is reachable from the same routing
table when the user asks how to install Rivermax or its
license.doca-setup — env preparation,
install verification, port-state checks (devlink dev show,
ip link), permission and group-membership requirements for
opening a doca_dev. This skill assumes its preconditions
are satisfied; the Rivermax-SDK + license preconditions are
layered on top.doca-version — canonical
DOCA version-handling rules. This skill's ## Version compatibility cross-links the four-way match rule and adds
the Rivermax-specific overlay (Rivermax SDK version is a
second axis; the capability set on this host is the
intersection of DOCA-side cap-query results and
Rivermax-side capabilities).doca-structured-tools-contract —
the bundle's structured-tools precedence rule (detect /
prefer / fall back / report). The Command appendix in
TASKS.md honors this contract.doca-programming-guide —
general DOCA programming patterns shared by every library:
the canonical pkg-config + meson build pattern, the
universal modify-a-shipped-sample first-app workflow, the
universal lifecycle, the cross-library DOCA_ERROR_*
taxonomy, and the program-side debug order. This skill
layers Rivermax specifics on top.doca-eth — the queue surface
that carries the packets a Rivermax stream produces or
consumes. DOCA Rivermax does not program the underlying
queue itself; it integrates with the queue programmed via
doca-eth. The two skills' lifecycles are independent.doca-flow — the steering
surface that decides which packets land on which queue.
DOCA Rivermax does not program steering itself; an empty
Rivermax input stream almost always means a missing or wrong
Flow rule (or a missing Rivermax license), not a Rivermax
bug.doca-debug — the
cross-cutting debug ladder (install / version / build /
link / runtime / program / driver). Rivermax-specific debug
(license precondition gaps, stream-type / packet-rate
capability mismatches, scheduling-discipline jitter
symptoms) overlays on top of that ladder.© NVIDIA, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 7 other files in skills/doca-rmax of NVIDIA/skills.
Open the folder on GitHubat commit 0e0d506
Doca Rmax next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Doca Rmax this skillNVIDIA/skills | 3.5k | — | ~4.6k | Automated safety check: Notes | Apache-2.0 | |
| Kernel ProfilingZJLi2013/awesome-kernel-skills | 102 | — | ~696 | Automated safety check: Pass | None | |
| LLM Torch Profiler Analysissgl-project/sglang | 37k | 2 repos | ~6.4k | Automated safety check: Pass | Apache-2.0 | |
| Megatron-LM Container and Dependency SetupNVIDIA/Megatron-LM | 18k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Nemoclaw Contributor Update DependenciesNVIDIA/NemoClaw | 23k | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | |
| Doc ReviewerNVlabs/alpasim | 1.3k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 |
ZJLi2013/awesome-kernel-skills
Profile GPU kernels using NCU (NVIDIA) or rocprof (AMD) to collect performance metrics.
sgl-project/sglang
Unified LLM torch-profiler triage skill for sglang, vllm, TensorRT-LLM, and TokenSpeed.
NVIDIA/Megatron-LM
Walks an agent through working inside the Megatron-LM CI container and changing dependencies with uv, so lock files resolve the same locally and in CI.
NVIDIA/NemoClaw
Audit and implement a NemoClaw dependency version upgrade, including Hermes and base images.
NVlabs/alpasim
Reviews recent code changes and checks if documentation needs updates.
CVCUDA/CV-CUDA
Find and safely apply per-operator refactoring / redundancy-reduction opportunities in a CV-CUDA operator (near-duplicate Tensor/VarShape kernels, reinvented shared utilities, dead code).
NVIDIA/skills
A skill your agent uses when the user wants to deploy, run, debug, tear down, or call the REST API of the RTVI-CV 2D detection / tracking microservice.
NVIDIA/skills
Generates, validates, compares and explains HOLOLINK_def.svh macro files for the HSB IP, using bundled Python scripts and asking before it writes anything.
NVIDIA/skills
Runs and validates an end-to-end Mission Control demo in a locally installed Isaac Sim, with a Nova Carter robot driven through a Python server.
NVIDIA/skills
Orchestrates defect image generation for PCBA, metal surface and glass inspection with NVIDIA Cosmos AnomalyGen on OSMO, from cold-start Day 0 to real-photo Day 1 labeling.
NVIDIA/skills
Orchestrates video data augmentation and auto-labeling workflows on OSMO, from flow selection and preflight checks to submission, monitoring and output download.
NVIDIA/skills
Runs NVIDIA TAO Data Services KPI analysis on object detection results, comparing predictions to ground truth and writing per-class precision, recall and AP to a CSV.
Works with
Categories
A skill your agent uses when the user is doing hands-on DOCA Rivermax work on a BlueField DPU or ConnectX host — standing up docarmaxinstream (receive) sessions for timing-precise media-over-IP…. Doca Rmax is an agent skill from NVIDIA/skills, published by the product's own GitHub organization. Use this skill when the user is doing hands-on DOCA Rivermax work on a BlueField DPU or ConnectX host — standing up docarmaxinstream (receive) sessions for timing-precise media-over-IP (SMPTE ST 2110 video/audio, market data, scientific feeds), confirming the Rivermax SDK + license precondition before any DOCA-side code, running docarmaxgetsupported capability queries, pairing with doca-eth queues and doca-flow steering, or debugging DOCAERROR from a Rivermax call.
Doca Rmax fits situations like: the user is doing hands-on DOCA Rivermax work on a BlueField DPU; connectX host — standing up docarmaxinstream (receive) sessions for timing-precise media-over-IP (SMPTE ST 2110 video/audio; scientific feeds); confirming the Rivermax SDK + license precondition before any DOCA-side code.
Run `npx skills add NVIDIA/skills --skill doca-rmax -a claude-code`. Or copy the skill folder (skills/doca-rmax in NVIDIA/skills) into .claude/skills/doca-rmax in your project. Claude Code loads it when a task matches its description.
Run `npx skills add NVIDIA/skills --skill doca-rmax -a codex`. Or copy the skill folder (skills/doca-rmax in NVIDIA/skills) into .agents/skills/doca-rmax in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add NVIDIA/skills --skill doca-rmax -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/doca-rmax, .gemini/skills/doca-rmax, .github/skills/doca-rmax and .opencode/skills/doca-rmax in your project.
SKILL.md names no scripts, command-line tools or credentials: Doca Rmax is instructions for the agent only. Compatibility (from SKILL.md): Requires DOCA SDK at /opt/mellanox/doca on Linux (Ubuntu 22.04/24.04 or RHEL/SLES) with a BlueField DPU or ConnectX NIC, AND the separately- installed NVIDIA Rivermax SDK with a valid Rivermax license readable by the user — DOCA does NOT bundle Rivermax. Reads the local install via `pkg-config doca-rmax`; route Rivermax SDK install/license questions to the public Rivermax guide. .
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (runs commands with sudo), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Doca Rmax is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.6k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Doca Rmax: Kernel Profiling (ZJLi2013/awesome-kernel-skills, 102 stars), LLM Torch Profiler Analysis (sgl-project/sglang, 37k stars), Megatron-LM Container and Dependency Setup (NVIDIA/Megatron-LM, 18k stars) and Nemoclaw Contributor Update Dependencies (NVIDIA/NemoClaw, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
NVIDIA (a GitHub organization, an official publisher) maintains it in NVIDIA/skills, which has 3,534 GitHub stars. The repository holds 380 skills in this directory. The repository was last updated on October 7, 2026.
Source: NVIDIA/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.